• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.555-562
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• 2012

This paper presents a hybrid method for improving the recognition performance, which is based on the nonlinear histogram equalization, features extraction, and statistical correlation of images. The nonlinear histogram equalization based on a logistic function is applied to adaptively improve the quality by adjusting the brightness of the image according to its intensity level frequency. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to rapidly and accurately express the similarity between the images. The local features based on independent component analysis(ICA) that is used to calculate the NCC, is also applied to statistically measure the correct similarity in each images. The proposed method has been applied to the problem for recognizing the 30-face images of 40*50 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the preprocessing, or the methods of conventional and adaptively modified histogram equalization, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.192-197
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• 2020

Multivariate processes, such as large scale power plants or chemical processes are operated in very hazardous environment, which can lead to significant human and material losses if a fault occurs. On-line monitoring technology, therefore, is essential to detect system faults. In this paper, the ICA-based fault detection method is conducted using three different multivariate process data. Fault detection procedure based on ICA is divided into off-line and on-line processes. The off-line process determines a threshold for fault detection by using the obtained dataset when the system is normal. And the on-line process computes statistics of query vectors measured in real-time. The fault is detected by comparing computed statistics and previously defined threshold. For comparison, the PCA-based fault detection method is also implemented in this paper. Experimental results show that the ICA-based fault detection method detects the system faults earlier and better than the PCA-based method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.6
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• pp.22-31
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• 2000

In this paper, we propose a method for removing noise components in the feature extraction process for robust speech recognition. This method is based on blind separation using independent component analysis (ICA). Given two noisy speech recordings the algorithm linearly separates speech from the unwanted noise signal. To apply ICA as closely as possible to the feature level for recognition, a new spectral analysis is presented. It modifies the computation of band energies by previously averaging out fast Fourier transform (FFT) points in several divided ranges within one met-scaled band. The simple analysis using sample variances of band energies of speech and noise, and recognition experiments showed its noise robustness. For noisy speech signals recorded in real environments, the proposed method which applies ICA to the new spectral analysis improved the recognition performances to a considerable extent, and was particularly effective for low signal-to-noise ratios (SNRs). This method gives some insights into applying ICA to feature levels and appears useful for robust speech recognition.

• Journal of the Korean Society of Food Science and Nutrition
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• v.35 no.6
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• pp.780-785
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• 2006

The composition analysis of various radish (Rapharnus sativus L.) leaves and the effects of drying condition on the quality characteristics of hot-air dried radish leaves were carried out by a response surface methodology. Independent variables put in drying temperature $(X_1)$ and drying time $(X_2)$, dependent variables put in color, calcium, iron, vitamin, etc. In the proximate composition of radish leaves by varieties, there were no significant differences in the ash, protein, lipid, calcium and iron content of samples, but there were significant differences in the vitamins, chlorophyll and color value of samples. The quality characteristics on dried radish leaves by central composite design, it was significant value on the moisture content, chlorophyll and color value according to drying temperature and drying times. But there were no significant differences in the contents of calcium $(31.41{\sim}35.80\;mg/g,\;dry\;base)$ and iron $(0.21{\sim}0.29\;mg/g\;dry\;base)$. The multiplex regression coefficients analysis were calculated with independent variables $(X_1,\;X_2)$ and dependent variables (moisture, chlorophyll, color value). The calculated coefficient correlations for the each samples were $R^2>0.97$. The effects of drying temperature were greater than drying time in the total chlorophyll content changes of radish leaves. Based on the present study, the optimum drying condition for the lowest color changes and effective reduction of moisture of radish leaves were expected to be $5{\sim}6$ hours at $70^{\circ}C$.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.9
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• pp.1477-1484
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• 2005

The effects of various seasoning components, pH of seasoning solution, heating time and storage temperature were investigated on the color and textural properties of the salted radish root (nanmooji) The effects of individual seasoning components in the salted radish root, additives of polyphosphate (AD3), citric acid (AD5), malic acid (AD2) delayed the color changes and softening more, compared to control soaked in water. On the other hand, additives of potassium sorbate (AD1), succinic acid (AD7), MSG (AD8), saccharin (AD6) accelerated the color changes and softening of the salted radish roots. The effects of pH of seasoning solution($X_1$), and heating time ($X_2$) were central composite design and response surface analysis. R- square represented dependent variables correlated independent variables ($X_1,\;X_2$), showed over 0.8 in the color and area value calculated thickness and firmness of salted radish root. Especially, R- square of 'b' represented 'yellow-green' was 0.899. And the result of crossing analysis of individual independent variables ($X_1,\;X_2$), showed that both independent variables had significant effects on the color and textural changes of the salted radish root. The salted radish root increased its color changes and softening, rapidly at $40^{\circ}C$, compared to the other storage temperatures at most storage periods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.33-42
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• 2005

Identifying color codes needs precise color information of their constituents, and is far from trivial because colors usually suffer severe distortions throughout the entire procedures from printing to acquiring image data. To accomplish accurate identification of colors, we need a reliable segmentation method to separate different color regions from each other, which would enable us to process the whole pixels in the region of a color statistically, instead of a subset of pixels in the region. Color image segmentation can be accomplished by performing edge detection on component image(s). In this paper, we separately detected edges on component images from RGB, HSI, and YIQ color models, and performed mathematical analyses and experiments to find out a pair of component images that provided the best edge image when combined. The best result was obtained by combining Y- and R-component edge images.

• 한국벤처창업학회:학술대회논문집
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• 2022.11a
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• pp.187-191
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• 2022

최근 기초화장품 트렌드로 클린 화장품, 비건 화장품 등이 브랜드별로 새롭게 출시되고 시장내 성장하고 있다. 한동안 화장품의 성분에 대한 관심과 영향이 커지면서 기능성화장품, 코스메슈티컬화장품, 더마화장품들이 신뢰를 얻고 인기가 있던 가운데, 효능 외의 요소를 소구하는 브랜드와 제품에 대한 관심이 커지고 있는 중이다. 본 연구는 이러한 변화에 있어 소비자의 라이프스타일과 소비가치의 상관관계가 영향이 있을 것으로 보고 이를 분석하고자 한다. 또한 ESG가 강조되는 사회 분위기 속에 클린 화장품 또는 비건 화장품의 소비가 일종의 자기표현의 욕구를 충족시켜주는 역할로써의 관계가 있는지도 알아보고자 한다. 따라서 기초 화장품을 사용하는 소비자들을 대상으로 라이프스타일과 자기표현욕구가 비건화장품 구매의도에 미치는 영향 및 소비가치를 매개변수로 하여 라이프스타일과 자기표현욕구와 구매의도 간의 영향을 살펴하고자 한다. 독립변수는 라이프스타일의 하위변수인 외모관리 지향형, 질적건강추구형으로 구분하였고, 자기표현욕구를 사용하였다. 설문조사는 대학생, 직장인, 주부등 20대부터 40대까지 연령층을 대상으로 진행하여 실증분석에 사용할 예정이다. SPSS v22.0을 사용하여 3단계 매개모형을 기반으로 회기분석할 예정이다.

• Applied Chemistry for Engineering
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• v.29 no.4
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• pp.446-451
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• 2018

Effective ingredients were extracted using wheat sprout with high levels of flavonoids, and the extraction process was optimized with a central composite design model. The response value of the central composite design model establishes the extraction yield and the content of the flavonoids. The main and interactive effects were then analyzed depending on independent variables such as the extraction time, the volume ratio of alcohol to ultrapure water, and the extraction temperature. The extraction time and temperature were relatively large for the extraction yield. For the total flavonoids, the extraction time was most significantly affected. Considering both the extraction yield and the content of the total flavonoids, optimal extraction conditions were as follows: the extraction time (2.44 h), volume ratio of alcohol to ultrapure water (50.00 vol%), extraction temperature ($54.41^{\circ}C$). Under these condition, the extraction yield was 30.14 wt% and the content of the total flavonoids was $35.37{\mu}g\;QE/mL\;dw$. From the actual experimental result, the extraction yield under this condition was 29.92 wt% and the content of the total flavonoids was $35.32{\mu}g\;QE/mL\;dw$, which had an error rate of 0.39% and 0.74%, respectively. This is a multi-analysis comprehensive analysis that analyzes two simultaneous values of responses, but is considered to be highly accurate and also provides an excellent reliability of the optimization process in this study.

• Korean Journal of Food Science and Technology
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• v.28 no.6
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• pp.1171-1176
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• 1996

The changes in volatiles of the model system were analyzed by GC and GC-MS before and after retorting. The GC data were analyzed statistically by applying the analysis of variance, and 42 peaks were selected at 5% significance level. Multivariate statistical analysis was performed with these 42 peaks as independent variables. Through the stepwise discriminant analysis, 8 peaks, which corresponded to the compounds such as 2-heptanone, cis-3-hexenal, 2-pentyl-furan, 1-methyl-trans-1,2-cyclohexanediol, 2-hexanone, 3-octanone, trans, trans-nona-2,4-dienal and 1-octen-3-ol, were obtained in sequence to distinguish the samples with and without retorting. The principal component analysis of a set of 8 independent variables resulted in 3 principal components which accounted for 96.1% of the variance, while the first principal component (PC 1) explained 76.5% of the total variance. In addition, through the factor analysis of the principal components, the peaks 11, 20 and 21 could be grouped togather in accordance with the direction and the size while the peaks 9, 33 and 39 constituted the second group in the direction.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.250-252
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• 2004

In this paper we apply several variations of independent component analysis( ICA) methods, such as spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA), to yeast cell cycle datasets, and compare their performance in finding components that result in gene clusters coherent with annotations and in extract ins meaningful temporal modes. It turns out that the results of tICA are superior to those of PCA, sICA, and stICA in terms of gene clustering and the temporal modes extracted by stICA highlights particular cellular processes.